Learning Outcomes

​A critical awareness of current problems and research issues in Data
Mining.

A comprehensive understanding of current advanced scholarship and research in data mining and how this may contribute to the effective design and implementation of data mining applications.​The ability to consistently apply knowledge concerning current data mining research issues in an original manner and produce work which is at the forefront of current developments in the sub-discipline of data mining.​A conceptual understanding sufficient to evaluate critically current research and advanced scholarship in data mining.​

Learning Strategy

Formal Lectures: Students will be expected to attend three hours of formal lectures in a typical week plus one hour supervised tutorial.

Private study: In a typical week students will be expected to devote six hours of unsupervised time to private study. The time allowed per week for private study will typically include three hours of time for reflection and consideration of lecture material and background reading, and three hours for completion of practical exercises.

Formal Lectures: Students will be expected to attend three hours of formal
lectures in a typical week plus one hour supervised tutorial.

Private study: In a typical week students will be expected to devote six
hours of unsupervised time to private study. The time allowed per week for
private study will typically include three hours of time for reflection and
consideration of lecture material and background reading, and three hours
for completion of practical exercises.